Dynamic Simulation and Resource Optimization of Urban Solid Waste Lifecycle Based on Digital Twin

The disconnect between urban solid waste management and urban planning represents a critical bottleneck for sustainable urban development. This paper proposes a digital twin-based method for dynamic simulation and resource optimization throughout the entire lifecycle of urban solid waste, establishing a collaborative platform integrating "Smart Urban Planning" and "Waste Resource Recovery" modules. Through 3D visual modeling, multi-dimensional simulation analysis (economic, engineering, and social benefits), and AI-driven dynamic matching of waste types with recycling technologies, the platform enables closed-loop management of construction and demolition waste—from generation and sorting to recycling and application. The system integrates BIM, GIS, IoT, and machine learning technologies to support real-time monitoring, dynamic early warning, and planning optimization, facilitating a shift from reactive governance to proactive optimization. Research demonstrates that the system significantly improves waste recycling rates, reduces carbon emissions and material costs in pilot areas, offering a replicable technical pathway for building "zero- waste cities."